AIMC Topic: Algorithms

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A graph-based gene selection method for medical diagnosis problems using a many-objective PSO algorithm.

BMC medical informatics and decision making
BACKGROUND: Gene expression data play an important role in bioinformatics applications. Although there may be a large number of features in such data, they mainly tend to contain only a few samples. This can negatively impact the performance of data ...

Magnetic Resonance Imaging Image Feature Analysis Algorithm under Convolutional Neural Network in the Diagnosis and Risk Stratification of Prostate Cancer.

Journal of healthcare engineering
This work aimed to explore the accuracy of magnetic resonance imaging (MRI) images based on the convolutional neural network (CNN) algorithm in the diagnosis of prostate cancer patients and tumor risk grading. A total of 89 patients with prostate can...

A Comparison among Different Machine Learning Pretest Approaches to Predict Stress-Induced Ischemia at PET/CT Myocardial Perfusion Imaging.

Computational and mathematical methods in medicine
Traditional approach for predicting coronary artery disease (CAD) is based on demographic data, symptoms such as chest pain and dyspnea, and comorbidity related to cardiovascular diseases. Usually, these variables are analyzed by logistic regression ...

DeepSENSE: Learning coil sensitivity functions for SENSE reconstruction using deep learning.

Magnetic resonance in medicine
PURPOSE: To improve the estimation of coil sensitivity functions from limited auto-calibration signals (ACS) in SENSE-based reconstruction for brain imaging.

Towards human-level performance on automatic pose estimation of infant spontaneous movements.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Assessment of spontaneous movements can predict the long-term developmental disorders in high-risk infants. In order to develop algorithms for automated prediction of later disorders, highly precise localization of segments and joints by infant pose ...

Path Planning for Autonomous Mobile Robots: A Review.

Sensors (Basel, Switzerland)
Providing mobile robots with autonomous capabilities is advantageous. It allows one to dispense with the intervention of human operators, which may prove beneficial in economic and safety terms. Autonomy requires, in most cases, the use of path plann...

Plugin Framework-Based Neuro-Symbolic Grounded Task Planning for Multi-Agent System.

Sensors (Basel, Switzerland)
As the roles of robots continue to expand in general, there is an increasing demand for research on automated task planning for a multi-agent system that can independently execute tasks in a wide and dynamic environment. This study introduces a plugi...

Multipath Lightweight Deep Network Using Randomly Selected Dilated Convolution.

Sensors (Basel, Switzerland)
Robot vision is an essential research field that enables machines to perform various tasks by classifying/detecting/segmenting objects as humans do. The classification accuracy of machine learning algorithms already exceeds that of a well-trained hum...

Using explainable machine learning to characterise data drift and detect emergent health risks for emergency department admissions during COVID-19.

Scientific reports
A key task of emergency departments is to promptly identify patients who require hospital admission. Early identification ensures patient safety and aids organisational planning. Supervised machine learning algorithms can use data describing historic...